Training Course on Research Design, Data Management and Statistical Analysis using Stata-Rwanda

About the Course

Conducting research is imperative for informed decision making. A sound knowledge about the methodology of conducting research and use of software for data management and analysis is very beneficial to new generation researchers. Stata statistical data software is a complete, integrated statistical software package that provides for data analysis, data management, and graphics. The course is aimed at researchers and other professionals who would like to strengthen their capacity using this statistical data analysis software. The training will enhance the knowledge and skills of the participants to analyse data in a fast, accurate and easier manner by using Stata software. Participants will know how to interpret and present the results.

Target Participants

This training course is ideal for researchers and data handling professionals such as M&E staff. The course is useful for other professionals who use data to make decisions. This course does not assume previous knowledge and competency in using Stata software.

What you will learn

By the end of the course the learner should be able to:

• Understand quantitative research approaches
• Easily collect high quality data using mobile devices such as tablets and phones.
• Clean their data for use in subsequent statistical analysis.
• Identify and fix errors in datasets.
• More quickly understand large and complex data sets with advanced statistical procedures that help ensure high accuracy and quality decision-making.
• Gain high level skills on statistical results interpretation and report writing.
• Write quality reports that arise from qualitative research process.

Course duration

5 days

Course Outline

Module 1: Introduction

Introduction to Research

• Introduction to research
• Different types of research
• Formulation of research problem statement
• Formulation of research hypothesis

Research Design

• Quantitative Research Approaches
• Qualitative Research Approaches

Sampling

• Sampling Techniques
• Sample size determination

Data Collection tools in Research

• Survey Questionnaire design
• FGD guide design
• KII guide design

Developing Research Protocol

• What is a research protocol?
• Basic concepts of a research protocol
• Structure of a research protocol

Introduction to Stata

• Introduction to Statistics Concepts
• Concepts and Software and technologies for Data Collection and Processing
• Stata Basics: Program window features, Data Structures and Types of Variables
• Data Management using Stata
• Output Management
• Basics of stata programming

Introduction to Mobile Data gathering

• Benefits of Mobile Applications
• Data and types of Data
• Introduction to  common mobile based data collection platforms
• Managing devices
• Challenges of Data Collection
• Data aggregation, storage and dissemination
• Questionnaire Design

Getting started in ODK

• Types of questions
• Data types for each question
• Types of questionnaire or Form logic
• Extended data types geoid, image and multimedia

 

Survey Authoring and Preparation of mobile phone for data collection

Survey Authoring

• Design forms using a web interface: ODK Build, Koboforms, PurcForms
• Preparing the mobile phone for data collection
• Installing applications: ODK Collect (using Google play)

Designing forms and advanced survey authoring

Designing forms manually: Using XLS Forms

• Introduction to XLS forms syntax
• New data types
• Notes and dates
• Multiple choice Questions
• Multiple Language Support
• Hints and Metadata
• Hands-on Exercise

Advanced survey Authoring

• Conditional Survey Branching
• Required questions
• Constraining responses
• Skip: Asking Relevant questions
• The specify other
• Grouping questions
• Skipping many questions at once (Skipping a section)
• Repeating a set of questions
• Special formatting
• Making dynamic calculations

Hosting survey data

• Online Hosting survey data (ODK Aggregate, Formhub, ona.io and KoboToolbox

Module 2: Descriptive Statistics

Measures of Variability and Central Tendency  

• Describing quantitative data
• Describing qualitative data (Tabulating data with Stata)

Stata Graphics

• Graphing quantitative data
• Graphing qualitative data

Module 3: Correlation, Chi-square and mean comparison analysis

Correlation  

• Correlation
• Subgroup Correlations
• Scatterplots of Data by Subgroups
• Overlay Scatterplots

Chi-Square 

• Goodness of Fit Chi Square All Categories Equal
• Goodness of Fit Chi Square Categories Unequal
• Chi Square for Contingency Tables

Comparing Means

• One Sample t-tests
• Paired Sample t-tests
• Independent Samples t-tests
• Comparing Means Using One-Way ANOVA 

Comparing Means Using Factorial ANOVA 

• Factorial ANOVA Using GLM Univariate
• Simple Effects

Module 4: Regression Analysis and Nonparametric Statistics 

Regression Analysis

• Assumptions of selected types of regression
• Linear regression; Binary logistic regression; ordered logistic regression; multinomial logistic regression and Poisson regression

Nonparametric Statistics 

• Mann-Whitney Test
• Wilcoxon’s Matched Pairs Signed-Ranks Test
• Kruskal-Wallis One-Way ANOVA
• Friedman’s Rank Test for k Related Samples

Module 5: Longitudinal/panel and Time series Analysis

Panel data analysis

• Introduction to panel data
• Longitudinal/panel data analysis

Time series Analysis

• Basic elements of time-series analysis
• Managing and summarizing time-series data
• Time series data analysis
• Introduction to forecasting